Quantitative Intelligence: New York 2025

Think you can outsmart the quants? Here’s your chance to prove it! The quantitative teams at S&P Global are using March Madness Historical DataSet (2002 to 2025) to generate predictive models for this year's NCAA Tournament brackets. You can submit your own bracket—either human- or computer-generated—up until 6:00 PM on the day of the event. Compare your predictions to the quants' models and compete for prizes and ultimate bragging rights!

With AI adoption accelerating and tech valuations soaring, some market observers have drawn comparisons to the dot-com bubble. But is today’s market really overinflated? Harry Mamaysky, a partner at QuantStreet Capital and Faculty Director of the Program for Financial Studies at Columbia Business School, will make the case that despite heightened valuations, the data indicate no imminent market correction on the horizon. Related research includes: U.S. vs International Stock Performance; Is It Possible to Forecast Large Market Selloffs?; Does High CAPE Predict Low Market Returns?; and The Mother of All Bubbles?

An earnings call Q&A is a dialogue between executives and sell-side analysts, with shareholders watching closely. When analysts ask about topics not addressed in the prepared remarks, it may suggest that executives either overlooked these issues or chose to avoid them. The way executives respond in these moments is equally revealing. Transparent answers build trust. Evasive answers raise concerns. Large Language vector embeddings of 192,000 earnings calls were used to score executives on: (1) proactiveness, proxied by how well the prepared remarks addressed analysts' questions, and (2) on-topic alignment, proxied by whether executives’ responses remained on-topic to the question. Combining both factors yielded 506 bps/year in a long/short portfolio. Dr. Dan will walk us through the research and corresponding ProntoNLP product; Henry Chiang (Quant Analyst, S&P Global Market Intelligence) will provide a hands-on demonstration of the project’s source code.

Tariffs create uncertainty for investors, executives, and policymakers. In an unpredictable environment, leveraging data effectively offers a competitive advantage. Here, we explore data-driven tools designed to monitor and anticipate the impacts of potential tariffs enacted during President Donald Trump’s second term in office. Drew Bowers (Senior Quant, S&P Global Market Intelligence),  speaks with leading executives: Ben Eisenberg, CEO of People Data Labs; Vishal Puri, CEO of RedGraphs; Ronen Feldman, CEO of ProntoNLP; Melissa Otto, Head of Visible Alpha Investment Research for S&P Global Market Intelligence.